AI Strategy & Advisory for Leadership

Who is this for?

Founders, CEOs, COOs, CTOs and business-unit heads at startups, scale-ups and enterprises who know AI matters but need a clear, unbiased view of where it pays off in their business. You do not need a data science team to start.

What problems does AI strategy consulting solve?

Most leadership teams face the same three problems: too many AI ideas and no way to rank them, vendors promising outcomes they cannot measure, and pilots that never reach production. We replace guesswork with a structured view of value, feasibility and risk, so every AI initiative has an owner, a budget and a KPI.

How does the engagement work?

1. Leadership alignment. A working session to agree on business goals, constraints and appetite for risk.
2. Opportunity mapping. We interview teams across product, operations, sales and support to build an inventory of AI use cases.
3. Value and feasibility scoring. Each use case is scored on impact, data readiness, cost and time-to-value.
4. Roadmap and KPI tree. We sequence the top opportunities into a 90-day plan and link each one to measurable KPIs.
5. Governance guardrails. We set practical policies for data privacy, model risk and responsible use.

Where does AI usually create value first?

In our experience, the fastest wins come from automating repetitive decisions in operations, giving sales teams better signals, and adding intelligent features to existing products. Our automated inventory replenishment project is a typical example: clear data, a measurable outcome and a short path to production.

What makes P26 different?

We are engineers as well as advisers. We have designed and shipped more than 30 software products, so our recommendations are grounded in what it actually takes to build, integrate and run AI systems, not just in slideware.